PROJECT SUMMARY/ABSTRACT Up to 10% of newborns need help breathing at birth, and up to 1% requires extensive cardiopulmonary resuscitation to survive. The frequency of neonatal resuscitation means that healthcare providers caring for newborns must be trained and ready to provide optimal resuscitation when needed. The gold standard for neonatal resuscitation training is simulation using neonatal simulation manikins. Providing effective training in neonatal resuscitation requires simulations that mimic human neonates in both form and function. The current generation of neonatal simulators lack adequate fidelity. Additionally, they cannot simulate neonatal physiology or provide automated feedback. The University of Washington (UW) Neonatal Education and Simulation-based Training (NEST) Program has performed a series of investigation on neonatal simulator fidelity and identified gaps in simulator fidelity. The UW Center for Research in Education and Simulation Technologies (CREST) Laboratory has previously developed a high-fidelity adult simulator that accurately replicates human anatomy to the finest details and includes automated feedback. In the proposed project, the NEST Program and CREST team will leverage their respective expertise to create the next generation neonatal simulator. The simulator will represent a quantum leap in fidelity and functionality over current neonatal simulators, and will greatly enhance neonatal resuscitation training. We propose to validate the next generation simulator by comparing it against two commercially available `high-fidelity' neonatal simulators and by performing a pilot study on neonatal endotracheal intubation success after training with the new simulator. The project is significant in that neonatal resuscitation is common, and that suboptimal resuscitation efforts can have devastating and lifelong consequences. Healthcare providers who attend neonatal deliveries are trained in neonatal resuscitation using simulators. These simulators must have high levels of structural and functional fidelity in order to serve as an effective training platform. Current simulators lack adequate fidelity. The project is innovative in that it will leverage the experience of the investigators in developing high-fidelity adult simulators towards the development of a next generation neonatal simulator. The simulator will be based on neonatal MRI scans and created using state of the art 3-D printing and tissue modeling techniques. The next generation simulator will contain integrated physiology software and provide automated feedback. The final product will be more lifelike than any current simulator and will enhance neonatal resuscitation training. Completion of the project will result in the creation of a next generation neonatal resuscitation trainer that will improve neonatal resuscitation training. This improved training will result in better neonatal resuscitation performance and ensure a smooth neonatal transition for a healthy beginning, and lay a foundation for optimal short- and long-term outcomes for all newborn infants